Performance Overview and Benchmark Context
Thinking Space 2 is a venture and growth equity fund managed by an AI-focused investment platform that targets early-stage and scaling startups in artificial intelligence, automation, and enterprise software. In the most recent public reporting period, the fund delivered a net internal rate of return that trailed several competing AI venture funds and public market indices. According to PitchBook data, the fund’s net multiple on invested capital was lower than the median for its vintage year cohort among AI-focused funds. This underperformance came despite a portfolio weighted toward generative AI and enterprise automation companies. The benchmark comparison included both top-quartile AI funds and broad technology venture indices. Investors used the fund as a case study in how concentrated AI exposure can amplify both upside and downside risk. The results were reported in the fund’s latest regulatory filings and third-party data aggregators. The fund’s managers acknowledged the gap in their public communications and highlighted a shift in allocation toward later-stage AI infrastructure plays. This context helps explain why several other funds and strategies have beaten Thinking Space 2 on a risk-adjusted basis. The performance gap is most visible in the public market equivalents and secondary sale prices of portfolio companies. The fund’s limited partners have requested more transparency around the specific companies and sectors driving the shortfall. The next sections detail the specific investors, funds, and market segments that have outperformed the fund in the same period.
External performance trackers show that several AI-focused venture funds posted higher net returns over the same period. The outperformance was driven by early bets on companies that later achieved high-value exits or public listings. Some competing funds concentrated on foundation model developers and AI infrastructure providers, which saw outsized valuation growth. Public market investors in AI-related exchange-traded funds and large-cap technology stocks also captured gains that exceeded the fund’s reported returns. The difference was especially pronounced during periods when public AI valuations surged on strong earnings and product adoption data. The fund’s managers attributed part of the gap to their longer holding periods and focus on pre-revenue and early-revenue companies. In contrast, some peer funds took larger positions in companies closer to profitability and revenue scale. This tactical difference contributed to the relative underperformance in net multiple and time-weighted return metrics. The data comes from third-party fund performance databases and regulatory filings available to limited partners and accredited investors. The comparison underscores the importance of portfolio construction and timing in AI venture investing.
Key Investors and Funds That Outperformed
Several institutional investors and fund managers have publicly reported stronger returns than Thinking Space 2 in the same vintage period. Andreessen Horowitz’s AI-focused funds, Sequoia Capital’s growth programs, and Lux Capital have been cited in third-party analyses as top performers in AI venture. These firms benefited from early positions in companies that later became leaders in generative AI, AI infrastructure, and enterprise AI applications. Some of these firms also used secondary sales and public market exits to lock in gains earlier than the fund in question. The outperformance was documented in fund performance reports, limited partner updates, and public statements by fund managers. In parallel, several corporate venture arms of large technology companies invested in AI startups that later achieved high valuations. These corporate investors often had strategic goals beyond financial returns, which allowed them to hold or double down on positions that underperformed financially. The contrast with Thinking Space 2 highlights how different investment mandates and exit strategies can lead to divergent results. The data points to a concentration of outperformance among a small number of well-capitalized AI-focused firms and their limited partners.
Among the specific entities that have beaten Thinking Space 2, several stand out due to their scale and public disclosures. Funds associated with a16z, Sequoia, and Lux Capital have been referenced in PitchBook and Crunchbase data as top quartile performers in AI venture. These firms often publish limited partner updates that include net IRR and MOIC figures, which are higher than the fund under review. In addition, several sovereign wealth funds and pension funds with dedicated AI venture allocations reported stronger returns over the same period.